| | --- |
| | base_model: microsoft/phi-2 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: V0422MADP7 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # V0422MADP7 |
| |
|
| | This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0616 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0003 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 16 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine_with_restarts |
| | - lr_scheduler_warmup_steps: 60 |
| | - num_epochs: 3 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 1.881 | 0.09 | 10 | 0.5408 | |
| | | 0.2348 | 0.18 | 20 | 0.1196 | |
| | | 0.1186 | 0.27 | 30 | 0.0956 | |
| | | 0.0994 | 0.36 | 40 | 0.0828 | |
| | | 0.0814 | 0.45 | 50 | 0.0769 | |
| | | 0.0868 | 0.54 | 60 | 0.0796 | |
| | | 0.0835 | 0.63 | 70 | 0.0785 | |
| | | 0.0822 | 0.73 | 80 | 0.0807 | |
| | | 0.0817 | 0.82 | 90 | 0.0692 | |
| | | 0.0773 | 0.91 | 100 | 0.0687 | |
| | | 0.0718 | 1.0 | 110 | 0.0666 | |
| | | 0.064 | 1.09 | 120 | 0.0650 | |
| | | 0.0681 | 1.18 | 130 | 0.0714 | |
| | | 0.0661 | 1.27 | 140 | 0.0664 | |
| | | 0.0598 | 1.36 | 150 | 0.0685 | |
| | | 0.0718 | 1.45 | 160 | 0.0616 | |
| | | 0.0645 | 1.54 | 170 | 0.0630 | |
| | | 0.0659 | 1.63 | 180 | 0.0667 | |
| | | 0.0625 | 1.72 | 190 | 0.0630 | |
| | | 0.0756 | 1.81 | 200 | 0.0679 | |
| | | 0.0669 | 1.9 | 210 | 0.0686 | |
| | | 0.0655 | 1.99 | 220 | 0.0691 | |
| | | 0.0567 | 2.08 | 230 | 0.0691 | |
| | | 0.0583 | 2.18 | 240 | 0.0607 | |
| | | 0.0551 | 2.27 | 250 | 0.0620 | |
| | | 0.0497 | 2.36 | 260 | 0.0661 | |
| | | 0.0542 | 2.45 | 270 | 0.0614 | |
| | | 0.0473 | 2.54 | 280 | 0.0621 | |
| | | 0.0443 | 2.63 | 290 | 0.0634 | |
| | | 0.0492 | 2.72 | 300 | 0.0624 | |
| | | 0.0537 | 2.81 | 310 | 0.0618 | |
| | | 0.0464 | 2.9 | 320 | 0.0616 | |
| | | 0.0526 | 2.99 | 330 | 0.0616 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.0.dev0 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.14.1 |
| |
|
